Crowd

Stream Ended

#DataOps is a requirement to get the ROI on your data science teams ... you'll never get the ROI of a data scientists' high salary unless you take away the time they spend on DataOps & put it into a focussed service: data science is a team sport & this team needs a DataOps player

@julielockner Our research is suggesting that data scientists are spending nearly half their time just finding and preparing data. If you can streamline that process via #dataops, you can immensely boost productivity.

An intelligent catalog that provides that self service, automates the governance and turns the output of the governance initiative into insight for the data scientists is at the heart of a good #dataops strategy.

So there is surely a part of this that can connect - AutoML will look at the data and suggest some algorithms, but also great AutoML platforms inspect the data, report on it, fix it (suggest), identify, record metadata, +++

I think it's a misconception that compliance needs to be "balanced" with business goals, as if they are opposing forces. Good governance and #DataOps methodology helps achieve compliance and help the business move faster.

Requlatory compliance with data privacy laws is one of the key drivers for Data Ops --- controlling where data is located and who has access ------ rules and policy integrated with authentication and controls

@SDobrin It's nothing less than shocking how many times I see clients waste an opportunity because they are just trying to check the compliance box - they do the hard work and lose the big time benefit beyond the obvious.